End of training
Browse files- README.md +176 -0
- benchmarks.shelve.bak +0 -0
- benchmarks.shelve.dat +0 -0
- benchmarks.shelve.dir +0 -0
- generation_config.json +6 -0
- logs/events.out.tfevents.1725468391.261a4d6fb516 +3 -0
README.md
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---
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base_model: gpt2
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datasets:
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- wikimedia/wikipedia
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library_name: Distily
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license: creativeml-openrail-m
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tags:
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- generated_from_trainer
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- Distily
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base_model_relation: finetune
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model-index:
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- name: distily_verify_update9
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results: []
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---
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# Summary
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Distilled with [Distily](https://github.com/lapp0/distily) library
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using teacher model [gpt2](https://huggingface.co/gpt2)
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on dataset [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia).
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment.
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# Model description
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More information needed
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# Intended uses & limitations
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More information needed
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-->
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# Model Architecture:
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- **Architecture**: `GPT2LMHeadModel`
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- **Total Parameters**: 81,912,576
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- **Data Type (dtype)**: torch.bfloat16
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- **Model Size**: 0.16 GB
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<details>
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<summary>Student Model Details</summary>
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```
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GPT2LMHeadModel(
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(transformer): GPT2Model(
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(wte): Embedding(50257, 768)
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(wpe): Embedding(1024, 768)
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(drop): Dropout(p=0.1, inplace=False)
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(h): ModuleList(
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(0-5): 6 x GPT2Block(
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(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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(attn): GPT2FlashAttention2(
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(c_attn): Conv1D()
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(c_proj): Conv1D()
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(attn_dropout): Dropout(p=0.1, inplace=False)
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(resid_dropout): Dropout(p=0.1, inplace=False)
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)
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(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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(mlp): GPT2MLP(
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(c_fc): Conv1D()
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(c_proj): Conv1D()
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(act): NewGELUActivation()
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(dropout): Dropout(p=0.1, inplace=False)
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)
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)
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)
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(ln_f): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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)
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(lm_head): Linear(in_features=768, out_features=50257, bias=False)
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)
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```
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</details>
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<br/>
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# Resource Usage
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- Max Train VRAM Use: 15.7096 GB
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- Available VRAM: 23.6497 GB
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- GPUs:
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- 1x NVIDIA GeForce RTX 4090
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- CPUs: 28
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- CPU Memory: 62.6429 GB
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- CPU Memory Bandwidth: 700 GB/s
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# Distillation (Teacher -> Student) Architecture Difference:
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- **Architecture**: `GPT2LMHeadModel` -> `GPT2LMHeadModel`
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- **Total Parameters**: 124,439,808 -> 81,912,576
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- **Data Type (dtype)**: torch.bfloat16 -> torch.bfloat16
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- **Model Size**: 0.24 GB -> 0.16 GB
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<details>
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<summary>Module Diff Details</summary>
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```diff
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--- teacher model modules
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+++ student model modules
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@@ -4,7 +4,7 @@
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(wpe): Embedding(1024, 768)
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(drop): Dropout(p=0.1, inplace=False)
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(h): ModuleList(
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- (0-11): 12 x GPT2Block(
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+ (0-5): 6 x GPT2Block(
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(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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(attn): GPT2FlashAttention2(
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(c_attn): Conv1D()
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```
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</details>
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<br/>
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# Train Dataset
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Trained on 3,221,668 tokens from the [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset.
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- Num Samples: `3,960`
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- Subset: `20231101.en`
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- Split: `train`
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# Training Objective
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```
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DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=5.0, loss_fn=raw_mse, layer_mapper=layer-2, norm=layernorm_teacher_only_affine, projector=orthogonal))
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```
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# Hyperparameters
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The following hyperparameters were used during training:
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<details>
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<summary>Expand</summary>
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- learning_rate: `0.0002`
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- train_batch_size: `16`
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- eval_batch_size: `8`
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- seed: `42`
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- optimizer: `Adam with betas=(0.9,0.999) and epsilon=1e-08`
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- lr_scheduler_type: `polynomial`
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- num_epochs: `1.0`
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- distillation_objective: `DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=5.0, loss_fn=raw_mse, layer_mapper=layer-2, norm=layernorm_teacher_only_affine, projector=orthogonal))`
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- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7fd8ec2cb7c0>`
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- student_model_name_or_path: `None`
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- student_config_name_or_path: `distilbert/distilgpt2`
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- student_model_config: `None`
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- reinitialize_weights: `None`
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- copy_teacher_modules: `[('lm_head', False)]`
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- student_model_as_bitnet: `False`
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- teacher_model_name_or_path: `gpt2`
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- teacher_load_in_8bit: `False`
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- teacher_load_in_4bit: `False`
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- dataset_uri: `wikimedia/wikipedia`
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- dataset_subset: `20231101.en`
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- dataset_split: `train`
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- dataset_column_name: `text`
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- dataset_sample_size: `4000`
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- dataset_test_size: `0.01`
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- gradient_accumulation_steps: `1`
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- weight_decay: `0.0`
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- max_grad_norm: `1.0`
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- warmup_ratio: `0.0`
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- warmup_steps: `0`
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- gradient_checkpointing: `True`
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</details>
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<br/>
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# Framework Versions
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- Distily 0.5.0
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- Transformers 4.44.2
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- Pytorch 2.3.0
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- Datasets 2.21.0
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benchmarks.shelve.bak
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benchmarks.shelve.dat
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benchmarks.shelve.dir
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.44.2"
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}
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logs/events.out.tfevents.1725468391.261a4d6fb516
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version https://git-lfs.github.com/spec/v1
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oid sha256:6ca34fbbe99c04600189c694e6b87b4a1ad1440ff1bf1dfa8396dbb7ceb572e5
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size 249
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